// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include #include #include #include #include "paddle/fluid/framework/op_info.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/variable.h" #include "paddle/fluid/pybind/pybind.h" #include "paddle/fluid/string/string_helper.h" std::map> op_ins_map = { {"layer_norm", {"X", "Scale", "Bias"}}, {"gru_unit", {"Input", "HiddenPrev", "Weight", "Bias"}}, {"label_smooth", {"X", "PriorDist"}}, {"assign", {"X"}}, }; std::map> op_passing_out_map = { {"sgd", {"ParamOut"}}, {"adam", {"ParamOut", "Moment1Out", "Moment2Out", "Beta1PowOut", "Beta2PowOut"}}, {"momentum", {"ParamOut", "VelocityOut"}}, {"batch_norm", {"MeanOut", "VarianceOut"}}, {"accuracy", {"Correct", "Total"}}, {"fill_constant", {"Out"}}, {"matmul", {"Out"}}}; // clang-format off const char* OUT_INITIALIZER_TEMPLATE = R"({"%s", {std::shared_ptr(new imperative::VarBase(tracer->GenerateUniqueName()))}})"; const char* OUT_DUPLICABLE_INITIALIZER_TEMPLATE = R"({"%s", ConstructDuplicableOutput(%s)})"; const char* INPUT_INITIALIZER_TEMPLATE = R"({"%s", {%s}})"; const char* INPUT_LIST_INITIALIZER_TEMPLATE = R"({"%s", %s})"; const char* INPUT_INITIALIZER_TEMPLATE_WITH_NULL = R"( if (%s != nullptr) { ins["%s"] = {%s}; } )"; const char* INPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST = R"( if (%s != nullptr) { ins["%s"] = %s; } )"; // if inputs is list, no need {} const char* ARG_OUT_NUM = R"(%sNum)"; const char* ARG_OUT_NUM_TYPE = R"(size_t )"; const char* VAR_TYPE = R"(std::shared_ptr)"; const char* VAR_LIST_TYPE = R"(std::vector>)"; const char* ARG_TEMPLATE = R"(const %s& %s)"; const char* RETURN_TUPLE_TYPE = R"(std::tuple<%s>)"; const char* RETURN_TYPE = R"(%s)"; const char* RETURN_TUPLE_TEMPLATE = R"(std::make_tuple(%s))"; const char* RETURN_LIST_TEMPLATE = R"(outs["%s"])"; const char* RETURN_TEMPLATE = R"(outs["%s"][0])"; const char* FUNCTION_ARGS = R"(%s, const py::args& args)"; const char* FUNCTION_ARGS_NO_INPUT = R"(const py::args& args)"; const char* OP_FUNCTION_TEMPLATE = R"( %s %s(%s) { framework::AttributeMap attrs; ConstructAttrMapFromPyArgs(&attrs, args); { py::gil_scoped_release release; auto tracer = imperative::GetCurrentTracer(); imperative::NameVarBaseMap outs = %s; imperative::NameVarBaseMap ins = %s; %s tracer->TraceOp("%s", ins, outs, attrs); return %s; } })"; const char* PYBIND_ITEM_TEMPLATE = R"( %s.def("%s", &%s);)"; // clang-format on static inline bool FindInputInSpecialization(const std::string& op_type, const std::string& in_name) { return op_ins_map[op_type].count(in_name); } static inline bool FindOutoutInSpecialization(const std::string& op_type, const std::string& out_name) { return op_passing_out_map[op_type].count(out_name); } static std::tuple, std::vector> GenerateOpFunctions(const std::string& module_name) { auto& op_info_map = paddle::framework::OpInfoMap::Instance().map(); std::vector op_function_list, bind_function_list; auto& all_kernels = paddle::framework::OperatorWithKernel::AllOpKernels(); for (auto& pair : op_info_map) { auto& op_info = pair.second; auto op_proto = op_info.proto_; if (op_proto == nullptr) { continue; } auto& op_type = op_proto->type(); // Skip ooerator which is not inherit form OperatorWithKernel, like while, // since only OperatorWithKernel can run in dygraph mode. if (!all_kernels.count(op_type)) { continue; } std::string input_args = ""; std::string ins_initializer = "{"; std::string ins_initializer_with_null = ""; std::string py_arg = ""; for (auto& input : op_proto->inputs()) { auto& in_name = input.name(); // skip those dispensable inputs, like ResidualData in conv2d if (input.dispensable() && !FindInputInSpecialization(op_type, in_name)) { continue; } const auto in_type = input.duplicable() ? VAR_LIST_TYPE : VAR_TYPE; auto input_arg = paddle::string::Sprintf(ARG_TEMPLATE, in_type, in_name); input_args += input_arg; input_args += ","; if (input.dispensable()) { const auto in_template = input.duplicable() ? INPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST : INPUT_INITIALIZER_TEMPLATE_WITH_NULL; ins_initializer_with_null += paddle::string::Sprintf(in_template, in_name, in_name, in_name); } else { const auto in_template = input.duplicable() ? INPUT_LIST_INITIALIZER_TEMPLATE : INPUT_INITIALIZER_TEMPLATE; ins_initializer += paddle::string::Sprintf(in_template, in_name, in_name); ins_initializer += ","; } } if (ins_initializer.back() == ',') { ins_initializer.pop_back(); } ins_initializer += "}"; if (input_args.back() == ',') { input_args.pop_back(); } // Generate outs initializer std::string outs_initializer = "{"; std::string return_type = ""; std::string return_str = ""; int outs_num = 0; for (auto& output : op_proto->outputs()) { if (output.dispensable()) { continue; } const auto out_type = output.duplicable() ? VAR_LIST_TYPE : VAR_TYPE; const auto return_template = output.duplicable() ? RETURN_LIST_TEMPLATE : RETURN_TEMPLATE; auto& out_name = output.name(); std::string out_initializer_str; if (FindOutoutInSpecialization(op_type, out_name)) { if (input_args != "") { input_args += ","; } input_args += out_type; input_args += out_name; const auto out_template = output.duplicable() ? INPUT_LIST_INITIALIZER_TEMPLATE : INPUT_INITIALIZER_TEMPLATE; out_initializer_str += paddle::string::Sprintf(out_template, out_name, out_name); } else { // There are few Operators that have duplicable output, like `Out` in // split op. We need to specify the number of variables for the // duplicable output, as the argument OutNum; if (output.duplicable()) { if (input_args != "") { input_args += ","; } auto out_num_str = paddle::string::Sprintf(ARG_OUT_NUM, out_name); input_args += ARG_OUT_NUM_TYPE; input_args += out_num_str; out_initializer_str = paddle::string::Sprintf( OUT_DUPLICABLE_INITIALIZER_TEMPLATE, out_name, out_num_str); } else { out_initializer_str = paddle::string::Sprintf(OUT_INITIALIZER_TEMPLATE, out_name); } } return_type += out_type; return_type += ","; return_str += paddle::string::Sprintf(return_template, out_name); return_str += ","; outs_num += 1; outs_initializer += out_initializer_str; outs_initializer += ","; } if (outs_initializer.back() == ',') { outs_initializer.pop_back(); return_type.pop_back(); return_str.pop_back(); } outs_initializer += "}"; if (outs_num == 0) { return_type = "void"; } if (outs_num > 1) { return_str = paddle::string::Sprintf(RETURN_TUPLE_TEMPLATE, return_str); return_type = paddle::string::Sprintf(RETURN_TUPLE_TYPE, return_type); } std::string function_args = ""; if (input_args == "") { function_args = paddle::string::Sprintf(FUNCTION_ARGS_NO_INPUT, input_args); } else { function_args = paddle::string::Sprintf(FUNCTION_ARGS, input_args); } std::string func_name = "imperative_" + op_type; // generate op funtcion body auto op_function_str = paddle::string::Sprintf( OP_FUNCTION_TEMPLATE, return_type, func_name, function_args, outs_initializer, ins_initializer, ins_initializer_with_null, op_type, return_str); // generate pybind item auto bind_function_str = paddle::string::Sprintf( PYBIND_ITEM_TEMPLATE, module_name, op_type, func_name); op_function_list.emplace_back(std::move(op_function_str)); bind_function_list.emplace_back(std::move(bind_function_str)); } return std::make_tuple(op_function_list, bind_function_list); } int main(int argc, char* argv[]) { if (argc != 2) { std::cerr << "argc must be 2" << std::endl; return -1; } std::vector headers{"\"paddle/fluid/imperative/tracer.h\""}; std::ofstream out(argv[1], std::ios::out); out << "#pragma once\n\n"; for (auto& header : headers) { out << "#include " + header + "\n"; } auto op_funcs = GenerateOpFunctions("m"); out << "namespace py = pybind11;" << "\n"; out << "namespace paddle {\n" << "namespace pybind {\n"; out << paddle::string::join_strings(std::get<0>(op_funcs), '\n'); out << "\n\n"; out << "inline void BindOpFunctions(pybind11::module *module) {\n" << " auto m = module->def_submodule(\"ops\");\n\n"; out << paddle::string::join_strings(std::get<1>(op_funcs), '\n'); out << "\n"; out << "}\n\n" << "} // namespace pybind\n" << "} // namespace paddle\n"; out.close(); return 0; }